Advances in Non-Invasive Blood Pressure Monitoring

This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminar...

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Detalles Bibliográficos
Autores principales: Quan, Xina, Liu, Junjun, Roxlo, Thomas, Siddharth, Siddharth, Leong, Weyland, Muir, Arthur, Cheong, So-Min, Rao, Anoop
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271585/
https://www.ncbi.nlm.nih.gov/pubmed/34206457
http://dx.doi.org/10.3390/s21134273
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author Quan, Xina
Liu, Junjun
Roxlo, Thomas
Siddharth, Siddharth
Leong, Weyland
Muir, Arthur
Cheong, So-Min
Rao, Anoop
author_facet Quan, Xina
Liu, Junjun
Roxlo, Thomas
Siddharth, Siddharth
Leong, Weyland
Muir, Arthur
Cheong, So-Min
Rao, Anoop
author_sort Quan, Xina
collection PubMed
description This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities.
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spelling pubmed-82715852021-07-11 Advances in Non-Invasive Blood Pressure Monitoring Quan, Xina Liu, Junjun Roxlo, Thomas Siddharth, Siddharth Leong, Weyland Muir, Arthur Cheong, So-Min Rao, Anoop Sensors (Basel) Article This paper reviews recent advances in non-invasive blood pressure monitoring and highlights the added value of a novel algorithm-based blood pressure sensor which uses machine-learning techniques to extract blood pressure values from the shape of the pulse waveform. We report results from preliminary studies on a range of patient populations and discuss the accuracy and limitations of this capacitive-based technology and its potential application in hospitals and communities. MDPI 2021-06-22 /pmc/articles/PMC8271585/ /pubmed/34206457 http://dx.doi.org/10.3390/s21134273 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Quan, Xina
Liu, Junjun
Roxlo, Thomas
Siddharth, Siddharth
Leong, Weyland
Muir, Arthur
Cheong, So-Min
Rao, Anoop
Advances in Non-Invasive Blood Pressure Monitoring
title Advances in Non-Invasive Blood Pressure Monitoring
title_full Advances in Non-Invasive Blood Pressure Monitoring
title_fullStr Advances in Non-Invasive Blood Pressure Monitoring
title_full_unstemmed Advances in Non-Invasive Blood Pressure Monitoring
title_short Advances in Non-Invasive Blood Pressure Monitoring
title_sort advances in non-invasive blood pressure monitoring
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271585/
https://www.ncbi.nlm.nih.gov/pubmed/34206457
http://dx.doi.org/10.3390/s21134273
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AT leongweyland advancesinnoninvasivebloodpressuremonitoring
AT muirarthur advancesinnoninvasivebloodpressuremonitoring
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